ABSTRACT
The number of individuals living with chronic conditions continues to rise. As a result, a significant emphasis has been placed on both improving their quality of life as well as decreasing the cost and burden of caring for them. One particularly promising avenue for achieving this is the use of wearable devices, as they have become both affordable and reliable in recognizing fitness activities. However, while the existing algorithms reliably recognize physically intensive activities (e.g., walking vs. swimming), they fail to recognize personal hygiene actives that have more subtle differences (e.g., brushing teeth vs. washing hands). This research aims to develop novel features and intelligent, multi-stage algorithms that can reliably recognize such personal hygiene activities for chronic care. Additionally, we aim to further supplement this activity recognition with personalized interventions that enable individuals to manage their own personal health.
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Index Terms
- Automatic Recognition of Hygiene Activities and Personalized Interventions for Chronic Care
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